Celik, I.; Abel, F.; Siehndel, P.: Adaptive faceted search on Twitter (2011)
0.00
0.001913537 = product of:
0.003827074 = sum of:
0.003827074 = product of:
0.007654148 = sum of:
0.007654148 = weight(_text_:a in 2221) [ClassicSimilarity], result of:
0.007654148 = score(doc=2221,freq=4.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.14413087 = fieldWeight in 2221, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0625 = fieldNorm(doc=2221)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- In the last few years, Twitter has become a powerful tool for publishing and discussing information. Yet, content exploration in Twitter requires substantial efforts and users often have to scan information streams by hand. In this paper, we approach this problem by means of faceted search. We propose strategies for inferring facets and facet values on Twitter by enriching the semantics of individual Twitter messages and present di erent methods, including personalized and context-adaptive methods, for making faceted search on Twitter more effective.
- Type
- a
